Our project, developed exclusively for HackSRM, aims to address the critical issue of battery explosions in electric vehicles (EVs). We have designed and implemented a predictive safety system that utilises sensor data, including atmospheric and internal vehicle temperatures, in conjunction with data provided by battery manufacturers. We have also developed an application for this project. Through various calculations, our system predicts the likelihood of a battery explosion and takes proactive measures to prevent such incidents.
Key Features:
1. Sensor Integration: Our system incorporates sensors capable of monitoring the atmospheric temperature surrounding the vehicle as well as the internal temperature within the vehicle's battery compartment. These sensors continuously gather real-time data, providing crucial inputs for our predictive model.
2. Data Analysis: We leverage the collected sensor data alongside information from the battery manufacturer, such as optimal operating temperatures and warning thresholds. Through analysis, we set a temperature barrier that indicates the potential risks of battery explosions.
3. Risk Prediction: By analysing the sensor data and cross-referencing it with the battery manufacturer's specifications, our predictive model determines the probability of a battery explosion. This risk assessment enables us to take proactive measures and alert the user to potential hazards.
4. Alerting and Mitigation: To ensure user safety, our system features an intuitive mobile application. If the predictive model detects an elevated risk of battery explosion, it sends real-time alerts to the user, highlighting the urgency of taking action. These alerts can prompt the driver to stop the vehicle, provide ventilation, or initiate other recommended safety protocols to mitigate the risk.